HawkEye 360 leverages M2M Machine Learning Connection from AWS to Enhance Maritime Security

HawkEye 360, the first company to use formation-flying satellites to create a new class of radio frequency (RF) data and analytics, have announced the development of maritime security to monitor vessel capabilities that combine HawkEye 360's robust RF geolocation services with a customized machine to machine (M2M) connected model developed through Amazon Web Services (AWS) Machine Learning (ML) Solutions Lab.

The capabilities will be integrated into the HawkEye 360 portfolio of products to leverage underlying vessel characteristics and behavior to predict whether a given vessel is likely to engage in similar activity as that of sanctioned vessels. With these machine learning-backed capabilities, the company will empower customers to cut through an ocean full of noise to obtain more critical insights from maritime RF data to improve outcomes and prevent illegal and illicit activities.

The algorithms used in the M2M connection will evaluate vessels' data and known interactions and vessel characteristics to generate insights into the complex connections involved in maritime vessel activity. This will provide analysts with a generalized view of maritime activity and the ability to detect, predict, and zoom in on the high-risk activity. This RF signals analysis and machine learning ability can help make the oceans a safe place by supporting various applications.